The invention relates generally to systems and methods for aligning the patient table and gantry in medical imaging systems.
For imaging systems, such as Positron Emission Tomography (PET) and Computed Tomography (CT) imagers, the alignment of a patient within the imaging area can be very important to the success of the imaging. Without correct placement of the patient in the scanning field of view, the imagers will gather data that is not properly aligned, leading to inaccurate images.
In PET imaging systems, these issues often arise when performing a multiple axial field of view (AFOV) study. In PET-CT studies, similar issues arise between the CT and PET scans. PET is a procedure that allows a physician to examine the heart, brain, and other organs, by producing images that show the molecular functioning of an organ or tissue. PET imagers include, among other components, a patient table with a cradle, a gantry and an operating workstation. In operation, the patient is placed in the cradle and driven into the gantry patient bore where the imaging takes place. The patient bore is lined by a series of detector rings that gather imaging data when the scanner is imaging. The detector rings typically utilize thousands of scintillator crystals to measure coincidence events when radiation is released into the scanning field of view. The data gathered is used to produce an image of the patient's body. In a multiple-AFOV study, where several snapshots of different regions of a patient's body are put together to get a complete image of the imaged region, when the patient is not aligned correctly on the cradle with respect to the detector rings, the image will show visible discontinuities, often at the axial field overlap regions.
Accordingly, there is a need for a more efficient and accurate method of aligning the table and gantry of an imaging system. The invention provides a method of aligning the table and gantry of an imaging system, as well as an imaging system with alignment features, that overcome the disadvantages of known systems and methods while offering features not present in known systems and methods.